Field effect transistor with controllable resistance

ABSTRACT

A method and resulting structures for a semiconductor device includes forming a source terminal of a semiconductor fin on a substrate. An energy barrier is formed on a surface of the source terminal. A channel is formed on a surface of the energy barrier, and a drain terminal is formed on a surface of the channel. The drain terminal and the channel are recessed on either sides of the channel, and the energy barrier is etched in recesses formed by the recessing. The source terminal is recessed using timed etching to remove a portion of the source terminal in the recesses formed by etching the energy barrier. A first bottom spacer is formed on a surface of the source terminal and a sidewall of the semiconductor fin, and a gate stack is formed on the surface of the first bottom spacer.

DOMESTIC PRIORITY

This application is a continuation of U.S. Non-Provisional applicationSer. No. 15/850,098, entitled “FIELD EFFECT TRANSISTOR WITH CONTROLLABLERESISTANCE,” filed Dec. 21, 2017, which is incorporated herein byreference in its entirety.

BACKGROUND

The present invention generally relates to fabrication methods andresulting structures for semiconductor devices. More specifically, thepresent invention relates to field effect transistors (FETs) withcontrollable resistance, particularly with resistance above apredetermined thresholds.

The present invention also generally relates to fabrication methods andresulting structures for a semiconductor device for use in artificialneural networks (ANNs) formed from crossbar arrays of two-terminalresistive processing units (RPUs) that provide local data storage andlocal data processing without the need for additional processingelements beyond the two-terminal RPU, thereby accelerating the ANN'sability implement algorithms such as matrix multiplication and the like.

“Machine learning” is used to broadly describe a primary function ofelectronic systems that learn from data. In machine learning andcognitive science, ANNs are a family of statistical learning modelsinspired by the biological neural networks of animals, and in particularthe brain. ANNs can be used to estimate or approximate systems andfunctions that depend on a large number of inputs and are generallyunknown. Crossbar arrays are high density, low cost circuitarchitectures used to form a variety of electronic circuits and devices,including ANN architectures, neuromorphic microchips and ultra-highdensity nonvolatile memory. A basic crossbar array configurationincludes a set of conductive row wires and a set of conductive columnwires formed to intersect the set of conductive row wires. Theintersections between the two sets of wires are separated by so-calledcrosspoint devices, which can be formed from thin film material.

SUMMARY

Embodiments of the present invention are directed to a method forfabricating a semiconductor device. A non-limiting example of the methodincludes forming a source terminal of a semiconductor fin on asubstrate. An energy barrier is formed on a surface of the sourceterminal. A channel is formed on a surface of the energy barrier, and adrain terminal is formed on a surface of the channel. The drain terminaland the channel are recessed on either sides of the channel, and theenergy barrier is etched in recesses formed by the recessing. The sourceterminal is recessed using timed etching to remove a portion of thesource terminal in the recesses formed by etching the energy barrier. Afirst bottom spacer is formed on a surface of the source terminal and asidewall of the semiconductor fin, and a gate stack is formed on thesurface of the first bottom spacer.

Embodiments of the present invention are directed to a semiconductordevice. A non-limiting example of the semiconductor device includes asource terminal and a drain terminal. The source terminal and the drainterminal are formed on either sides of a channel region designated on asubstrate. An energy barrier is adjacent to the source terminal and thechannel region, and a conductive gate stack is formed over the channelregion.

Embodiments of the invention are directed to semiconductor device. Anon-limiting example of the semiconductor device includes asemiconductor fin formed on a substrate. The semiconductor fin includesan energy barrier between a source terminal and a channel region of thesemiconductor fin. A conductive gate is formed over the channel regionof the semiconductor fin, and a bottom spacer is formed between theconductive gate and the substrate.

Embodiments of the invention are directed to semiconductor device. Anon-limiting example of the semiconductor device includes asemiconductor fin formed on a substrate. The semiconductor fin includesa source terminal that is doped using a first dopant, a drain terminalthat is doped using a second dopant at a first concentration, and achannel that is doped using the second dopant at a second concentration.The second concentration is lower than the first concentration.

Additional technical features and benefits are realized through thetechniques of the present invention. Embodiments and aspects of theinvention are described in detail herein and are considered a part ofthe claimed subject matter. For a better understanding, refer to thedetailed description and to the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The specifics of the exclusive rights described herein are particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features and advantages ofthe embodiments of the invention are apparent from the followingdetailed description taken in conjunction with the accompanying drawingsin which:

FIG. 1 depicts a simplified diagram of input and output connections of abiological neuron;

FIG. 2 depicts a known simplified model of the biological neuron shownin FIG. 1;

FIG. 3 depicts a known simplified model of an ANN incorporating thebiological neuron model shown in FIG. 2;

FIG. 4 depicts a simplified block diagram of a known weight updatemethodology;

FIG. 5 is a diagram of an ANN including arrays of weights in accordancewith the one or more embodiments;

FIG. 6 depicts a cross bar array of RPU devices according to embodimentsof the present invention, along with voltage sequences illustrating theoperation of the RPU;

FIG. 7 depicts a flowchart for an example method of fabricating a planardiffusion FET 700 according to one or more embodiments of the presentinvention;

FIG. 8 depicts a cross sectional view of an example SOI wafer 800according to one or more embodiments of the present invention;

FIG. 9 depicts an example FET structure according to one or moreembodiments of the present invention;

FIG. 10 depicts an example FET structure according to one or moreembodiments of the present invention subsequent to forming thesource/drain and energy barrier;

FIG. 11 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention;

FIG. 12 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention;

FIG. 13 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention;

FIG. 14 depicts an example FET structure according to one or moreembodiments of the present invention subsequent to forming the gatestack;

FIG. 15 depicts an embodiment to store the weight in the FET 800according to one or more embodiments of the present invention;

FIG. 16 depicts an embodiment to store the weight in the FET 800according to one or more embodiments of the present invention;

FIG. 17 depicts another embodiment to store the weight in the FET 800according to one or more embodiments of the present invention;

FIG. 18 depicts an example semiconductor structure for the FET accordingto one or more embodiments of the present invention;

FIG. 19 depicts an effect of the energy barrier in the III-V HBFETstructure 1800 described herein on the current level according to one ormore embodiments of the present invention;

FIG. 20 depicts an effect of the energy barrier in the SiGe—Si HBFETstructure 1800 described herein on the current level according to one ormore embodiments of the present invention;

FIG. 21 depicts an embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention;

FIG. 22 depicts an embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention;

FIG. 23 depicts another embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention;

FIG. 24 depicts an example RPU array 600 using vertical semiconductorstructure for the HBFET according to one or more embodiments of thepresent invention;

FIG. 25 depicts a substrate preparation of the HBFET 2400 area accordingto one or more embodiments of the present invention;

FIG. 26 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention;

FIG. 27 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention;

FIG. 28 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention;

FIG. 29 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention;

FIG. 30 depicts a cross-sectional view of a VFET structure after topspacer opening and top drain formation during an intermediate operationof the exemplary method of fabricating a semiconductor device accordingto one or more embodiments of the invention;

FIG. 31 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention;

FIG. 32 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention;

FIG. 33 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention;

FIG. 34 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention;

FIG. 35 depicts connections between the HBFET 2400 and the RPU array 600according to one or more embodiments of the present invention;

FIG. 36 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention to connect the HBFET 2400 to the RPU array 600;

FIG. 37 depicts an embodiment of a tunnel FET 3700 according to one ormore embodiments of the present invention;

FIG. 38 depicts an effect of the tunnel FET structure described hereinon the current level according to one or more embodiments of the presentinvention;

FIG. 39 depicts an effect of the tunnel FET structure described hereinon the current level according to one or more embodiments of the presentinvention;

FIG. 40 depicts an effect of the energy barrier in the tunnel FETstructure described herein on the current level according to one or moreembodiments of the present invention;

FIG. 41 depicts an embodiment to store the weight in the tunnel FET 3700according to one or more embodiments of the present invention;

FIG. 42 depicts an embodiment to store the weight in the tunnel FET 3700according to one or more embodiments of the present invention;

FIG. 43 depicts another embodiment to store the weight in the tunnel FET3700 according to one or more embodiments of the present invention;

FIG. 44 depicts a forward pass using the RPU array with the asymmetricFET structures described herein according to one or more embodiments ofthe present invention;

FIG. 45 depicts a backward pass using the RPU array with the asymmetricFET structures described herein according to one or more embodiments ofthe present invention;

FIG. 46 depicts an example symmetric semiconductor structure for thediffusion FET according to one or more embodiments of the presentinvention; and

FIG. 47 depicts an example symmetric semiconductor structure for theHBFET according to one or more embodiments of the present invention.

The diagrams depicted herein are illustrative. There can be manyvariations to the diagram or the operations described therein withoutdeparting from the spirit of the invention. For instance, the actionscan be performed in a differing order or actions can be added, deletedor modified.

In the accompanying figures and following detailed description of thedescribed embodiments, the various elements illustrated in the figuresare provided with two, three, or four digit reference numbers. Withminor exceptions, the leftmost digit(s) of each reference numbercorrespond to the figure in which its element is first illustrated.

DETAILED DESCRIPTION

Various embodiments of the invention are described herein with referenceto the related drawings. Alternative embodiments of the invention can bedevised without departing from the scope of this invention. Variousconnections and positional relationships (e.g., over, below, adjacent,etc.) are set forth between elements in the following description and inthe drawings. These connections and/or positional relationships, unlessspecified otherwise, can be direct or indirect, and the presentinvention is not intended to be limiting in this respect. Accordingly, acoupling of entities can refer to either a direct or an indirectcoupling, and a positional relationship between entities can be a director indirect positional relationship. Moreover, the various tasks andprocess steps described herein can be incorporated into a morecomprehensive procedure or process having additional steps orfunctionality not described in detail herein.

The following definitions and abbreviations are to be used for theinterpretation of the claims and the specification. As used herein, theterms “comprises,” “comprising,” “includes,” “including,” “has,”“having,” “contains” or “containing,” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, acomposition, a mixture, process, method, article, or apparatus thatcomprises a list of elements is not necessarily limited to only thoseelements but can include other elements not expressly listed or inherentto such composition, mixture, process, method, article, or apparatus.

Additionally, the term “exemplary” is used herein to mean “serving as anexample, instance or illustration.” Any embodiment or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments or designs. The terms “at least one”and “one or more” can be understood to include any integer numbergreater than or equal to one, i.e. one, two, three, four, etc. The terms“a plurality” can be understood to include any integer number greaterthan or equal to two, i.e. two, three, four, five, etc. The term“connection” can include both an indirect “connection” and a direct“connection.”

The terms “about,” “substantially,” “approximately,” and variationsthereof, are intended to include the degree of error associated withmeasurement of the particular quantity based upon the equipmentavailable at the time of filing the application. For example, “about”can include a range of ±8% or 5%, or 2% of a given value.

For the sake of brevity, conventional techniques related tosemiconductor device and integrated circuit (IC) fabrication may or maynot be described in detail herein. Moreover, the various tasks andprocess steps described herein can be incorporated into a morecomprehensive procedure or process having additional steps orfunctionality not described in detail herein. In particular, varioussteps in the manufacture of semiconductor devices andsemiconductor-based ICs are well known and so, in the interest ofbrevity, many conventional steps will only be mentioned briefly hereinor will be omitted entirely without providing the well-known processdetails.

Turning now to an overview of technologies that are more specificallyrelevant to aspects of the present invention, in contemporarysemiconductor device fabrication processes, a large number ofsemiconductor devices, such as field effect transistors (FETs), arefabricated on a single wafer. Further, some non-planar transistorarchitectures, such as vertical field effect transistors (VFETs), employsemiconductor fins and side-gates that can be contacted outside theactive region, resulting in increased device density and some increasedperformance over lateral devices. In VFETs the source to drain currentflows in a direction that is perpendicular to a major surface of thesubstrate. For example, in a known VFET configuration a major substratesurface is horizontal and a vertical fin or nanowire extends upward fromthe substrate surface. The fin or nanowire forms the channel region ofthe transistor. A source region and a drain region are situated inelectrical contact with the top and bottom ends of the channel region,while the gate is disposed on one or more of the fin or nanowiresidewalls.

There are challenges, however, in providing VFETs with equal or superiorperformance characteristics to lateral devices. In a VFET the contact tothe bottom source/drain (S/D) is formed from the top of the structuresuch that the bottom S/D contact overlaps the gate. This verticallystacked configuration in combination with the reduced footprint of VFETsresults in a large parasitic capacitance between the gate and the S/Dregion of the substrate. Parasitic capacitance between two conductors(also known as conductor-to-conductor capacitance) is a function of thelength and thickness of the conductors as well as the distanceseparating the conductors. Parasitic capacitance contributes toundesired device effects such as resistive-capacitive (RC) delay, powerdissipation, and cross-talk. RC delay refers to the delay in signalspeed or propagation experienced in a circuit as a function of theproduct of the resistance and capacitance of the circuit components.Unfortunately, parasitic capacitance continues to increase as devicedimensions and component spacing shrinks to meet increasing demands forsmaller electronic devices. Conventional approaches to reducing theparasitic capacitance between the gate and the S/D region of the VFETsubstrate have not been wholly successful. In a conventional VFET, forexample, a thin bottom spacer is formed between the gate and the bottomS/D region to somewhat mitigate the parasitic capacitance. The thicknessof this thin bottom spacer in conventional VFETs, however, isconstrained by channel length requirements. Consequently, the parasiticcapacitance remains relatively high, and better solutions are needed.

Turning now to an overview of aspects of the present invention, one ormore embodiments of the invention provide methods and structuresconfigured to provide a FETs with controllable resistance. Such FETsimprove systems, such as electronic circuits and devices that are usedto implement artificial neural networks (ANN). Particularly, a technicalchallenge in implementing ANNs is the learning speed requirement fordeep neural network application (described further). The aspects of thepresent invention provide technical solutions that address suchtechnical challenges by facilitating an analog weight update componentthat satisfies the learning speed requirement.

Further, a brief description of ANN implementations using resistiveprocessing unit (RPU) arrays is provided. The aspects of the presentinvention facilitate providing semiconductor devices that can be used insuch ANN implementations, for example, to store weights at crosspointsof the RPU array. It should be noted that the semiconductor devicesdescribed herein can be used in ways other than the above example(s).

It is understood in advance that although one or more embodiments of theinvention are described in the context of biological neural networkswith a specific emphasis on modeling brain structures and functions,implementation of the teachings recited herein are not limited tomodeling a particular environment. Rather, embodiments of the presentinvention are capable of modeling any type of environment, including forexample, weather patterns, arbitrary data collected from the internet,and the like, as long as the various inputs to the environment can beturned into a vector. Accordingly, although embodiments of the presentinvention are directed to electronic systems, for ease of reference andexplanation various aspects of the electronic systems are describedusing neurological terminology such as neurons, plasticity and synapses,for example. It will be understood that for any discussion orillustration herein of an electronic system, the use of neurologicalterminology or neurological shorthand notations are for ease ofreference and are meant to cover the neuromorphic, ANN equivalent(s) ofthe described neurological function or neurological component.

Artificial neural networks (ANNs) can be used to estimate or approximatesystems and functions that depend on a large number of inputs and aregenerally unknown. Neural networks use a class of algorithms based on aconcept of interconnected “neurons.” In a typical neural network,neurons have a given activation function that operates on the inputs. Bydetermining proper connection weights (a process also referred to as“training”), a neural network achieves efficient recognition of adesired patterns, such as images and characters. Oftentimes, theseneurons are grouped into “layers” in order to make connections betweengroups more obvious and to each computation of values. Training theneural network is a computationally intense process.

ANNs are often embodied as so-called “neuromorphic” systems ofinterconnected processor elements that act as simulated “neurons” andexchange “messages” between each other in the form of electronicsignals. Similar to the so-called “plasticity” of synapticneurotransmitter connections that carry messages between biologicalneurons, the connections in ANNs that carry electronic messages betweensimulated neurons are provided with numeric weights that correspond tothe strength or weakness of a given connection. The weights can beadjusted and tuned based on experience, making ANNs adaptive to inputsand capable of learning. For example, an ANN for handwriting recognitionis defined by a set of input neurons which can be activated by thepixels of an input image. After being weighted and transformed by afunction determined by the network's designer, the activations of theseinput neurons are then passed to other downstream neurons, which areoften referred to as “hidden” neurons. This process is repeated until anoutput neuron is activated. The activated output neuron determines whichcharacter was read.

Crossbar arrays, also known as crosspoint arrays or crosswire arrays,are high density, low cost circuit architectures used to form a varietyof electronic circuits and devices, including ANN architectures,neuromorphic microchips and ultra-high density nonvolatile memory. Abasic crossbar array configuration includes a set of conductive rowwires and a set of conductive column wires formed to intersect the setof conductive row wires. The intersections between the two sets of wiresare separated by so-called crosspoint devices, which can be formed fromthin film material.

Crosspoint devices, in effect, function as the ANN's weightedconnections between neurons. Nanoscale devices, for example memristorshaving “ideal” conduction state switching characteristics, are oftenused as the crosspoint devices in order to emulate synaptic plasticitywith high energy efficiency. The conduction state (e.g., resistance) ofthe ideal memristor material can be altered by controlling the voltagesapplied between individual wires of the row and column wires. Digitaldata can be stored by alteration of the memristor material's conductionstate at the intersection to achieve a high conduction state or a lowconduction state. The memristor material can also be programmed tomaintain two or more distinct conduction states by selectively settingthe conduction state of the material. The conduction state of thememristor material can be read by applying a voltage across the materialand measuring the current that passes through the target crosspointdevice.

In order to limit power consumption, the crosspoint devices of ANN chiparchitectures are often designed to utilize offline learning techniques,wherein the approximation of the target function does not change oncethe initial training phase has been resolved. Offline learning allowsthe crosspoint devices of crossbar-type ANN architectures to besimplified such that they draw very little power.

Notwithstanding the potential for lower power consumption, executingoffline training can be difficult and resource intensive because it istypically necessary during training to modify a significant number ofadjustable parameters (e.g., weights) in the ANN model to match theinput-output pairs for the training data. Accordingly, simplifying thecrosspoint devices of ANN architectures to prioritize power-saving,offline learning techniques typically means that training speed andtraining efficiency are not optimized.

Instead of utilizing the traditional digital model of manipulating zerosand ones, ANNs create connections between processing elements that aresubstantially the functional equivalent of the core system functionalitythat is being estimated or approximated. For example, IBM™'s SYNAPSE™computer chip is the central component of an electronic neuromorphicmachine that attempts to provide similar form, function and architectureto the mammalian brain. Although the IBM SyNapse computer chip uses thesame basic transistor components as conventional computer chips, itstransistors are configured to mimic the behavior of neurons and theirsynapse connections. The IBM SyNapse computer chip processes informationusing a network of just over one million simulated “neurons,” whichcommunicate with one another using electrical spikes similar to thesynaptic communications between biological neurons. The IBM SyNapsearchitecture includes a configuration of processors (i.e., simulated“neurons”) that read a memory (i.e., a simulated “synapse”) and performsimple operations. The communications between these processors, whichare typically located in different cores, are performed by on-chipnetwork routers.

A general description of how a typical ANN operates will now be providedwith reference to FIGS. 1, 2 and 3. As previously noted herein, atypical ANN models the human brain, which includes about one hundredbillion interconnected cells called neurons. FIG. 1 depicts a simplifieddiagram of a biological neuron 102 having pathways 104, 106, 108, 110that connect it to upstream inputs 112, 114, downstream outputs 116 anddownstream “other” neurons 118, configured and arranged as shown. Eachbiological neuron 102 sends and receives electrical impulses throughpathways 104, 106, 108, 110. The nature of these electrical impulses andhow they are processed in biological neuron 102 are primarilyresponsible for overall brain functionality. The pathway connectionsbetween biological neurons can be strong or weak. When a given neuronreceives input impulses, the neuron processes the input according to theneuron's function and sends the result of the function to downstreamoutputs and/or downstream “other” neurons.

Biological neuron 102 is modeled in FIG. 2 as a node 202 having amathematical function, f(x) depicted by the equation shown in FIG. 2.Node 202 takes electrical signals from inputs 212, 214, multiplies eachinput 212, 214 by the strength of its respective connection pathway 204,206, takes a sum of the inputs, passes the sum through a function, f(x),and generates a result 216, which can be a final output or an input toanother node, or both. In the present description, an asterisk (*) isused to represent a multiplication. Weak input signals are multiplied bya very small connection strength number, so the impact of a weak inputsignal on the function is very low. Similarly, strong input signals aremultiplied by a higher connection strength number, so the impact of astrong input signal on the function is larger. The function f(x) is adesign choice, and a variety of functions can be used. An example designchoice for f(x) is the hyperbolic tangent function, which takes thefunction of the previous sum and outputs a number between minus one andplus one.

FIG. 3 depicts a simplified ANN model 300 organized as a weighteddirectional graph, wherein the artificial neurons are nodes (e.g., 302,308, 316), and wherein weighted directed edges (e.g., m1 to m20) connectthe nodes. ANN model 300 is organized such that nodes 302, 304, 306 areinput layer nodes, nodes 308, 310, 312, 314 are hidden layer nodes andnodes 316, 318 are output layer nodes. Each node is connected to everynode in the adjacent layer by connection pathways, which are depicted inFIG. 3 as directional arrows having connection strengths m1 to m20.Although only one input layer, one hidden layer and one output layer areshown, in practice, multiple input layers, hidden layers and outputlayers can be provided.

Similar to the functionality of a human brain, each input layer node302, 304, 306 of ANN 300 receives inputs x1, x2, x3 directly from asource (not shown) with no connection strength adjustments and no nodesummations. Accordingly, y1=f(x1), y2=f(x2) and y3=f(x3), as shown bythe equations listed at the bottom of FIG. 3. Each hidden layer node308, 310, 312, 314 receives its inputs from all input layer nodes 302,304, 306 according to the connection strengths associated with therelevant connection pathways. Thus, in hidden layer node 308,y4=f(m1*y1+m5*y2+m9*y3), wherein * represents a multiplication. Asimilar connection strength multiplication and node summation isperformed for hidden layer nodes 310, 312, 314 and output layer nodes316, 318, as shown by the equations defining functions y5 to y9 depictedat the bottom of FIG. 3.

ANN model 300 processes data records one at a time, and it “learns” bycomparing an initially arbitrary classification of the record with theknown actual classification of the record. Using a training methodologyknows as “backpropagation” (i.e., “backward propagation of errors”), theerrors from the initial classification of the first record are fed backinto the network and used to modify the network's weighted connectionsthe second time around, and this feedback process continues for manyiterations. In the training phase of an ANN, the correct classificationfor each record is known, and the output nodes can therefore be assigned“correct” values. For example, a node value of “1” (or 0.9) for the nodecorresponding to the correct class, and a node value of “0” (or 0.1) forthe others. It is thus possible to compare the network's calculatedvalues for the output nodes to these “correct” values, and to calculatean error term for each node (i.e., the “delta” rule). These error termsare then used to adjust the weights in the hidden layers so that in thenext iteration the output values will be closer to the “correct” values.

There are many types of neural networks, but the two broadest categoriesare feed-forward and feedback/recurrent networks. ANN model 300 is anon-recurrent feed-forward network having inputs, outputs and hiddenlayers. The signals can only travel in one direction. Input data ispassed onto a layer of processing elements that perform calculations.Each processing element makes its computation based upon a weighted sumof its inputs. The new calculated values then become the new inputvalues that feed the next layer. This process continues until it hasgone through all the layers and determined the output. A thresholdtransfer function is sometimes used to quantify the output of a neuronin the output layer.

A feedback/recurrent network includes feedback paths, which mean thatthe signals can travel in both directions using loops. All possibleconnections between nodes are allowed. Because loops are present in thistype of network, under certain operations, it can become a non-lineardynamical system that changes continuously until it reaches a state ofequilibrium. Feedback networks are often used in associative memoriesand optimization problems, wherein the network looks for the bestarrangement of interconnected factors.

The speed and efficiency of machine learning in feed-forward andrecurrent ANN architectures depend on how effectively the crosspointdevices of the ANN crossbar array perform the core operations of typicalmachine learning algorithms. Although a precise definition of machinelearning is difficult to formulate, a learning process in the ANNcontext can be viewed as the problem of updating the crosspoint deviceconnection weights so that a network can efficiently perform a specifictask. The crosspoint devices typically learn the necessary connectionweights from available training patterns. Performance is improved overtime by iteratively updating the weights in the network. Instead offollowing a set of rules specified by human experts, ANNs “learn”underlying rules (like input-output relationships) from the givencollection of representative examples. Accordingly, a learning algorithmcan be generally defined as the procedure by which learning rules areused to update and/or adjust the relevant weights.

The three main learning algorithm paradigms are supervised, unsupervisedand hybrid. In supervised learning, or learning with a “teacher,” thenetwork is provided with a correct answer (output) for every inputpattern. Weights are determined to allow the network to produce answersas close as possible to the known correct answers. Reinforcementlearning is a variant of supervised learning in which the network isprovided with only a critique on the correctness of network outputs, notthe correct answers themselves. In contrast, unsupervised learning, orlearning without a teacher, does not require a correct answer associatedwith each input pattern in the training data set. It explores theunderlying structure in the data, or correlations between patterns inthe data, and organizes patterns into categories from thesecorrelations. Hybrid learning combines supervised and unsupervisedlearning. Parts of the weights are usually determined through supervisedlearning, while the others are obtained through unsupervised learning.

As previously noted herein, in order to limit power consumption, thecrosspoint devices of ANN chip architectures are often designed toutilize offline learning techniques, wherein the approximation of thetarget function does not change once the initial training phase has beenresolved. Offline learning allows the crosspoint devices ofcrossbar-type ANN architectures to be simplified such that they drawvery little power.

Notwithstanding the potential for lower power consumption, executingoffline training can be difficult and resource intensive because it istypically necessary during training to modify a significant number ofadjustable parameters (e.g., weights) in the ANN model to match theinput-output pairs for the training data. FIG. 4 depicts a simplifiedillustration of a typical read-process-write weight update operation,wherein CPU/GPU cores (i.e., simulated “neurons”) read a memory (i.e., asimulated “synapse”) and perform weight update processing operations,then write the updated weights back to memory. Accordingly, simplifyingthe crosspoint devices of ANN architectures to prioritize power-saving,offline learning techniques typically means that training speed andtraining efficiency are not optimized.

FIG. 5 illustrates an artificial neural network (ANN) architecture 500.During feed-forward operation, a set of input neurons 502 each providean input voltage in parallel to a respective row of weights 504. Aweight 504 is a crosspoint device, such as an RPU. The weights 504 eachhave a settable resistance value, such that a current output flows fromthe weight 504 to a respective hidden neuron 506 to represent theweighted input. The current output by a given weight is determined asI=V/r, where V is the input voltage from the input neuron 502 and r isthe set resistance of the weight 504. The current from each weight addscolumn-wise and flows to a hidden neuron 506. A set of reference weights507 have a fixed resistance and combine their outputs into a referencecurrent that is provided to each of the hidden neurons 506. Becauseconductance values can only be positive numbers, some referenceconductance is needed to encode both positive and negative values in thematrix. The currents produced by the weights 504 are continuously valuedand positive, and therefore the reference weights 507 are used toprovide a reference current, above which currents are considered to havepositive values and below which currents are considered to have negativevalues. By facilitating the resistance value (r) of FETs to becontrollable, and controllable above a predetermined threshold (e.g. 10MΩ, 90 MΩ, 99 MΩ, 100 MΩ etc.) the technical solutions described hereinfacilitate using the FETs as the weight storage component at acrosspoint in the RPU array. Alternatively, a capacitor at eachcrosspoint stores the weight and the FET facilitates reading the valuefrom the capacitor.

The hidden neurons 506 use the currents from the array of weights 504and the reference weights 507 to perform some calculation. The hiddenneurons 506 then output a voltage of their own to another array ofweights 507. This array performs in the same way, with a column ofweights 504 receiving a voltage from their respective hidden neuron 506to produce a weighted current output that adds row-wise and is providedto the output neuron 508.

It should be understood that any number of these stages can beimplemented, by interposing additional layers of arrays and hiddenneurons 506. It should also be noted that some neurons can be constantneurons 509, which provide a constant voltage to the array. The constantneurons 509 can be present among the input neurons 502 and/or hiddenneurons 506 and are only used during feed-forward operation.

During back propagation, the output neurons 508 provide a voltage backacross the array of weights 504. The output layer compares the generatednetwork response to training data and computes an error. The error isapplied to the array as a voltage pulse, where the height and/orduration of the pulse is modulated proportional to the error value. Inthis example, a row of weights 504 receives a voltage from a respectiveoutput neuron 508 in parallel and converts that voltage into a currentwhich adds column-wise to provide an input to hidden neurons 506. Thehidden neurons 506 provide combine the weighted feedback signal with aderivative of its feed-forward calculation and stores an error valuebefore outputting a feedback signal voltage to its respective column ofweights 504. This back propagation travels through the entire network500 until all hidden neurons 506 and the input neurons 502 have storedan error value.

During weight updates, the input neurons 502 and hidden neurons 506apply a first weight update voltage forward and the output neurons 508and hidden neurons 506 apply a second weight update voltage backwardthrough the network 500. The combinations of these voltages create astate change within each weight 504, causing the weight 504 to take on anew resistance value. In this manner, the weights 504 can be trained toadapt the neural network 500 to errors in its processing. It should benoted that the three modes of operation, feed forward, back propagation,and weight update, do not overlap with one another.

As previously noted herein, to accommodate the learning speedrequirement for deep neural network application, the embodiments of thepresent invention provide an analog weight update component. Forexample, Resistive processing unit (RPU) in a cross-bar structure canenable parallel matrix multiplication and improve the neural networktraining speed. For large neural networks which usually contains >1million weight elements, each weight element is to be highly resistive,in the order of 10 MΩ, and the resistance needs to be changeable. FieldEffect transistor (FET), whose resistance can be well controlled by gatepotential, is a candidate as a weight element for implementing such aneural network. However, the resistance of modern FETs is in the rangeof 10 kΩ, therefore, it has to be increased ˜1000 times to meet thespecification. The embodiments of the present invention address suchtechnical challenges and provide FET structures that meet suchspecifications, thus facilitating implementation of the neural networksusing RPU cross-bar structures.

Turning now to an overview of the present invention, one or moreembodiments are directed to a programmable resistive crosspointcomponent referred to herein as a crosspoint device, or a resistiveprocessing unit (RPU), which provides local data storage functionalityand local data processing functionality. In other words, when performingdata processing, the value stored at each RPU is updated in parallel andlocally, which eliminate the need to move relevant data in and out of aprocessor and a separate storage element. Additionally, the local datastorage and local data processing provided by the described RPUsaccelerate the ANN's ability to implement algorithms such as matrixmultiplication and the like. Accordingly, implementing a machinelearning ANN architecture having the described RPU enables theimplementation that optimize the speed, efficiency and power consumptionof the ANN. The described RPU and resulting ANN architecture improveoverall ANN performance and enable a broader range of practical ANNapplications.

The RPU in the cross-bar structure enables parallel matrixmultiplication and substantially enhances the neural network trainingspeed. For large neural networks which usually contain more than 1million weight elements, each weight element has to be highly resistive,in the order of 10 MΩ, and the resistance has to be changeable. Forexample, FETs, whose resistance can be well controlled by gatepotential, is one candidate as a weight element for the neural network.However, the resistance of modern FET is in the range of 10 kΩ,substantially lower than what is required for implementing the largeneural networks (almost 1000 times lower to meet the specifications).Such technical challenges are addressed by the invention(s) describedherein by facilitating weight storage elements that have an increasedcontrollable resistance in the substantially higher ranges, such as 10MΩ-100 MΩ.

In one or more examples, two charge transport changes in the FETstructure substantially increase the controllable resistance of a FET,enabling the FET to be used as the weight storage element in an RPUarray.

FIG. 6 depicts a cross bar array of RPU devices according to embodimentsof the present invention, along with voltage sequences illustrating theoperation of the RPU. FIG. 6 is a diagram of a two-dimensional (2D)crossbar array 600 that performs forward matrix multiplication, backwardmatrix multiplication and weight updates according to embodiments of thepresent invention. Crossbar array 600 is formed from a set of conductiverow wires 802, 804, 806 and a set of conductive column wires 808, 810,812, and 814 that intersect the set of conductive row wires 802, 804,and 806. The intersections between the set of row wires and the set ofcolumn wires are separated by RPUs, which are shown in FIG. 6 asresistive elements each having its own adjustable/updateable resistiveweight, depicted as σ11, σ21, σ31, σ41, σ12, σ22, σ32, σ42, σ13, σ23,σ33 and σ43, respectively. For ease of illustration, only one RPU 820 islabeled with a reference number in FIG. 6. In forward matrixmultiplication, the conduction state (i.e., the stored weights) of theRPU can be read by applying a voltage across the RPU and measuring thecurrent that passes through the RPU.

Input voltages V1, V2, V3 are applied to row wires 802, 804, 806,respectively. Each column wire 808, 810, 812, 814 sums the currents I1,I2, I3, I4 generated by each RPU along the particular column wire. Forexample, as shown in FIG. 6, the current I4 generated by column wire 814is according to the equation I4=V1σ41+V2σ42+V3σ43. Thus, array 600computes the forward matrix multiplication by multiplying the valuesstored in the RPUs by the row wire inputs, which are defined by voltagesV1, V2, V3. The backward matrix multiplication is very similar. Inbackward matrix multiplication, voltages are applied at column wires808, 810, 812, 814 then read from row wires 802, 804, 806. For weightupdates, which are described in greater detail below, voltages areapplied to column wires and row wires at the same time, and theconductance values stored in the relevant RPU devices all update inparallel. Accordingly, the multiplication and addition operationsrequired to perform weight updates are performed locally at each RPU 820of array 600 using the RPU device itself plus the relevant row or columnwire of array 600.

Continuing with the diagram of FIG. 6, in accordance with one or moreembodiments, the operation of a positive weight update methodology forRPU 820 and its corresponding weight σ33 at the intersection ofconductive row wire 806 and conductive column wire 812 will now beprovided. Update generator circuitry (not shown) is provided at theperiphery of crossbar array 600 and used as a peripheral “translator” inorder to generate necessary voltage pulses in the form of stochastic bitstreams that are applied to all RPUs of 2D crossbar array 600.

Accordingly, referring to the ANN implemented using a crosspoint arrayincluding RPUs as described herein, in the array, the value of theresistance (or conductance) of each node determines the coupling betweennodes, where a node is represented by an RPU device in the array.Further, upon training the crosspoint array according to the ANN, theresistance (or conductance) will be different from device to device,depending on the desired coupling. For training a neural network, it isnecessary to actively adjust the resistance values. Once the training iscomplete, the resistance values remain fixed during operation of thecrosspoint array circuit, until training begins for a new task.

Methods for forming a semiconductor device and semiconductor devices inaccordance with embodiments of the invention are described in detailbelow by referring to the accompanying drawings.

Various embodiments of the present invention are described herein withreference to the related drawings. Alternative embodiments can bedevised without departing from the scope of this invention. It is notedthat various connections and positional relationships (e.g., over,below, adjacent, etc.) are set forth between elements in the followingdescription and in the drawings. These connections and/or positionalrelationships, unless specified otherwise, can be direct or indirect,and the present invention is not intended to be limiting in thisrespect. Accordingly, a coupling of entities can refer to either adirect or an indirect coupling, and a positional relationship betweenentities can be a direct or indirect positional relationship. As anexample of an indirect positional relationship, references in thepresent description to forming layer “A” over layer “B” includesituations in which one or more intermediate layers (e.g., layer “C”) isbetween layer “A” and layer “B” as long as the relevant characteristicsand functionalities of layer “A” and layer “B” are not substantiallychanged by the intermediate layer(s).

For purposes of the description hereinafter, the terms “upper,” “lower,”“right,” “left,” “vertical,” “horizontal,” “top,” “bottom,” andderivatives thereof shall relate to the described structures andmethods, as oriented in the drawing figures. The terms “overlying,”“atop,” “on top,” “positioned on” or “positioned atop” mean that a firstelement, such as a first structure, is present on a second element, suchas a second structure, wherein intervening elements such as an interfacestructure can be present between the first element and the secondelement. The term “direct contact” means that a first element, such as afirst structure, and a second element, such as a second structure, areconnected without any intermediary conducting, insulating orsemiconductor layers at the interface of the two elements. It should benoted, the term “selective to,” such as, for example, “a first elementselective to a second element,” means that a first element can be etchedand the second element can act as an etch stop. The term “about” isintended to include the degree of error associated with measurement ofthe particular quantity based upon the equipment available at the timeof filing the application. For example, “about” can include a range of±8% or 5%, or 2% of a given value.

By way of background, however, a more general description of thesemiconductor device fabrication processes that can be utilized inimplementing one or more embodiments of the present invention will nowbe provided. Although specific fabrication operations used inimplementing one or more embodiments of the present invention can beindividually known, the described combination of operations and/orresulting structures of the present invention are unique. Thus, theunique combination of the operations described in connection with thefabrication of a semiconductor device having closely packed verticaltransistors with reduced contact resistance according to the presentinvention utilize a variety of individually known physical and chemicalprocesses performed on a semiconductor (e.g., silicon) substrate, someof which are described in the immediately following paragraphs.

In general, the various processes used to form a micro-chip that will bepackaged into an IC fall into four general categories, namely, filmdeposition, removal/etching, semiconductor doping andpatterning/lithography. Deposition is any process that grows, coats, orotherwise transfers a material onto the wafer. Available technologiesinclude physical vapor deposition (PVD), chemical vapor deposition(CVD), plasma-enhanced chemical vapor deposition (PECVD),electrochemical deposition (ECD), molecular beam epitaxy (MBE) and morerecently, and atomic layer deposition (ALD) among others.

Removal/etching is any process that removes material from the wafer.Examples include etch processes (either wet or dry), andchemical-mechanical planarization (CMP), and the like. A wet etchprocess, such as a buffered hydrofluoric acid (BHF) etch, is a materialremoval process that uses liquid chemicals or etchants to removematerials from a surface. A dry etch process, such as reactive ionetching (RIE), uses chemically reactive plasma to remove a material,such as a masked pattern of semiconductor material, by exposing thematerial to a bombardment of ions that dislodge portions of the materialfrom the exposed surface. The plasma is generated under low pressure(vacuum) by an electromagnetic field.

Semiconductor doping is the modification of electrical properties bydoping, for example, transistor sources and drains, generally bydiffusion and/or by ion implantation. These doping processes arefollowed by furnace annealing or by rapid thermal annealing (RTA).Annealing serves to activate the implanted dopants. Films of bothconductors (e.g., poly-silicon, aluminum, copper, etc.) and insulators(e.g., various forms of silicon dioxide, silicon nitride, etc.) are usedto connect and isolate transistors and their components. Selectivedoping of various regions of the semiconductor substrate allows theconductivity of the substrate to be changed with the application ofvoltage. By creating structures of these various components, millions oftransistors can be built and wired together to form the complexcircuitry of a modern microelectronic device.

Semiconductor lithography is the formation of three-dimensional reliefimages or patterns on the semiconductor substrate for subsequenttransfer of the pattern to the substrate. In semiconductor lithography,the patterns are formed by a light sensitive polymer called aphoto-resist. To build the complex structures that make up a transistorand the many wires that connect the millions of transistors of acircuit, lithography and etch pattern transfer steps are repeatedmultiple times. Each pattern being printed on the wafer is aligned tothe previously formed patterns and slowly the conductors, insulators andselectively doped regions are built up to form the final device.

In one or more embodiments, the resistive elements are formed usingsemiconductor strips, such as polysilicon. The strips can be doped, tocontrol the resistivity of the semiconductor. Typically, the resistancevalue can be varied using strips of different dimensions. However, theconventional method can include tailoring multiple lithographic masks toensure that contacts are made with the ends of the strips.

Turning now to an overview of aspects of the present invention, one ormore embodiments provide methods of fabricating a semiconductor devicehaving a crosspoint array that includes multiple crosspoint devices withcontrollable high resistance values (>10 MΩ). In one or moreembodiments, optical lithography and/or electron beam lithography isused followed by selective plasma etching for fabricating the crosspointarray that includes multiple crosspoint devices.

FIG. 7 depicts a flowchart for an example method of fabricating a planardiffusion FET according to one or more embodiments of the presentinvention. The method includes providing a substrate 805, such as asilicon-on-insulator (SOI) wafer or any other semiconductor substrate(702).

FIG. 8 depicts a cross sectional view of an example wafer 805 used tofabricate a semiconductor device 800 according to one or moreembodiments of the present invention. In one or more examples, the wafer800 is lightly doped. In case the wafer 800 is an SOI, it can furtherinclude an insulator layer (e.g., a buried oxide (BOX) layer or othersuitable insulator layer) on the substrate 805.

Referring back to FIG. 7, the fabrication method for the planar FETfurther includes, patterning a source region 825 and a channel region827 for an FET structure in the substrate 805 (704).

FIG. 9 depicts an example FET structure according to one or moreembodiments of the present invention. The FET structure includes shallowtrench isolation (STI) regions 820 to define a device region within thesemiconductor layer 805. In one or more examples patterning and dopingprocess is performed that to form the source and drain regions 825 and827. Between the source and drain region would be the designated channelregion 850. The patterning process is performed by optical lithographyand the doping process by ion implementation and high temperatureannealing.

Further, the fabrication method (FIG. 7) includes forming an energybarrier region 830 (706).

FIG. 10 depicts an example FET structure according to one or moreembodiments of the present invention subsequent to forming the energybarrier 830. In addition to the source 825 and the drain 827, the energybarrier 830 is added between the source 825 and channel 850 bypatterning and partially doping the channel 850. The energy barrier 830is created in a region between the source 825 (or drain 827) and thechannel 850 for the predetermined size Ld.

The energy barrier 830 is created by heavier doping of the region of theenergy barrier 830 compared to the doping performed on the channel 850.For example, in case of ion implantation, the energy barrier 830 isdoped heavier (P+) than the channel 850 (P−), and the source 825 and thedrain 827 are N doped, thus forming an N-P-N FET. In other embodiments,a P-N-P FET is fabricated by implanting ions to dope the energy barrier830 heavier (N+) compared to the channel 850 (N−), and implanting thesource 825 and the drain 827 to be doped (P).

The doped regions (825, 827, and 830) can be formed in the substrate 805by a variety of methods, such as, implantation and plasma doping. In oneor more examples, they may be etched away and regrown with differentmethods, for example, in-situ doped epitaxy, doped following theepitaxy, and the like. The doped regions can be formed by any suitableprocess, including but not limited to, ultrahigh vacuum chemical vapordeposition (UHVCVD), rapid thermal chemical vapor deposition (RTCVD),metalorganic chemical vapor deposition (MOCVD), low-pressure chemicalvapor deposition (LPCVD), limited reaction processing CVD (LRPCVD), andMBE. In some embodiments, the doped regions include epitaxialsemiconductor materials grown from gaseous or liquid precursors.

FIG. 11 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention. Plot 1110 depicts an ON state of adiffusion FET and plot 1120 depicts an OFF state. In both plots, avalence band 1135 and a conduction band 1145 are shown. Typically, in adiffusion FET, the “ON” state current is dominated by the diffusioncurrent from the source 825 to the drain 827, via the channel 850. Inthe FET structure described herein, the current level is dominated bythe energy barrier height (labeled H) between the source 825 and theextra doping region 830. This barrier height can be modulated by thegate voltage through the sidewall spacer. The spacer is an insulatinglayer, preferable to be high-k dielectric. Charge on the gate generatesfringing field in the spacer, through which modulates the height of theenergy barrier.

FIG. 12 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention. The illustrated plot shows acomparison of a first transfer characteristic 1210 of a typical FET,without the energy barrier 830, and a second transfer characteristic1220 of a diffusion FET with the energy barrier 830. As can be seen thediffusion FET with the energy barrier 830 has a lower current. It shouldbe noted that the plots in FIG. 12 illustrate result values fromspecific example scenario, and that in other examples, the plots can bedifferent from those illustrated.

FIG. 13 depicts an effect of the energy barrier in the FET structuredescribed herein on the current level according to one or moreembodiments of the present invention. The illustrated plot showsresistance of the diffusion FET with the energy barrier 830 as afunction of gate voltage with different lengths (Ld) of the energybarrier region 830 with the extra doping. For example, the plot depictsthe resistance of the FET as Ld is set at 16 nm (1330), 18 nm (1320),and 20 nm (1310), respectively. It should be noted that the value of Ldcan be different from the above exemplary values, causing the FETresistance to change in a different manner than what is shown in FIG.13.

Referring back to FIG. 7, the fabrication method for the planar FETfurther includes, conventional processing in order to form a gate stack840 (708).

FIG. 14 depicts an example FET structure according to one or moreembodiments of the present invention subsequent to forming the gatestack. The FET structure further includes a gate stack 840 (e.g., a gatedielectric layer 841, a gate conductor layer 842 on the gate dielectriclayer 841 and a cap layer 843, such as a nitride cap layer, on the gateconductor layer 842) over the designated channel region 850 within thedevice region. Typically, the gate dielectric layer is an oxide ofsilicon, but any material suitable for use as a gate dielectric can beused. Examples of other gate dielectric materials include HfO₂ andAl₂O₃. The gate conductor layer 842 can be composed of metal and/orpolysilicon or any other material(s) that serves as the gate electrodefor the semiconductor device 800.

Further, gate sidewall spacers 845 are formed on opposing sides of thegate stack 840 (710). In one or more examples, source/drain extensionregions and/or halo regions can also be formed, depending upon theintegration scheme (e.g., late or early). The details of theabove-mentioned conventional processing are well-known and are omittedto allow the reader to focus on the salient aspects of the embodimentsdescribed herein.

Further, in order to store the weight in the FET 800, the gate potentialof the FET device 800 is kept at a certain value. This can be realizedthrough different structures.

FIG. 15 depicts an embodiment to store the weight in the FET 800according to one or more embodiments of the present invention. The FET800 is connected with a capacitor 1510. The charge is stored at theplate to provide the gate voltage, the charge stored beingrepresentative of the weight stored at the crosspoint in the RPU array600. It should be noted that only some of the parts of the FET device800 are shown in FIG. 15 for simplicity of illustration.

FIG. 16 depicts an embodiment to store the weight in the FET 800according to one or more embodiments of the present invention. A chargestorage layer 1610, such as a floating gate is added to the gate stack840. The charge can be stored in the charge storing layer 1610 toprovide the gate voltage. The charge storing layer 1610 is composed ofpolysilicon. In one or more examples, another the gate dielectric layer841 is added after the charge storing layer 1610, followed by thefurther layers in the gate stack 840, such as the conductive materiallayer 842 for the electrode.

FIG. 17 depicts another embodiment to store the weight in the FET 800according to one or more embodiments of the present invention. Here, thegate stack includes the gate dielectric layer 841 followed by a firstconductive material layer 842. A ferroelelectric material layer 1710 isadded subsequently, such as composed of hafnium dioxide (HfO2). Thepolarization of the ferroelectric layer 1710 induces electrical field inthe spacer to modulate the height of energy barrier in layer 830.Further, the gate stack 840 includes a second conductive material layer842 to form the control gate electrode. The first conductive materiallayer 842 addresses a technical challenge of depolarization of theferroelelectric material layer 1710.

Further, in one or more examples, the energy barrier 830 between thesource 825 and the channel 850 is modulated in an indirect way, throughthe side wall 845 dielectrics. For example, the side walls 845 can becomposed of hafnium dioxide (HfO2) and titanium nitride (TiN)depositions are used to form a high-k dielectric layer. Theferroelectric layer 1710 and the side walls 845 thus form a metal highdielectric constant (MHK) gate stack.

Thus, the one or more planar diffusion FET semiconductor devicesdescribed herein provide technical solutions to the technical challengesof providing controllable resistance, particularly above 10 MΩ. Suchplanar diffusion FETs can be used in crosspoint devices that are part ofan RPU array 600 that performs matrix multiplications, such as forimplementing ANNs.

Further, according to one or more embodiments of the present invention,the semiconductor FET is a hetero-barrier FET (HBFET), for example, witha (III-V structure). FIG. 18 depicts an example semiconductor structurefor the FET according to one or more embodiments of the presentinvention. The hetero-barrier FET (III-V) structure 1800 (as shown) issimilar to the diffusion-FET described earlier, but instead of using adoped region as the energy barrier region 830 near source, thehetero-barrier FET incorporates a heterojunction material.

For example, in the HBFET 1800 the source 825, drain 827, and channel850 are composed of a III-V small bandgap channel such as indium galliumarsenide (InGaAs) or gallium arsenide antimonide (GaAsSb) to improvecomplementary metal oxide semiconductor (CMOS) transistor switchingspeed. Further, the energy barrier 830 is composed of a wide-bandgapmaterial, such as indium phosphide (InP) to form a hetero-barrier. TheHBFET 1800 further includes the gate stack 840 with side walls composedof spacer material such as Si3N4 that facilitates hetero-barriermodulation thru fringe-fields. In one or more examples, the regions aredoped to form a NPN HBFET such that—the source 825 and drain 827 aredoped N+, and the energy barrier 830 and the channel 850 are doped P−.It should be noted that in other examples the doping can be different toform a PNP HBFET.

FIG. 19 depicts an effect of the energy barrier in the III-V HBFETstructure 1800 described herein on the current level according to one ormore embodiments of the present invention. Plot 1910 depicts an ON stateof the HBFET and plot 1920 depicts an OFF state of the HBFET. In bothplots, a valence band 1935 and a conduction band 1945 are shown.Typically, in a diffusion FET, the “ON” state current is dominated bythe diffusion current from the source 825 to the drain 827, via thechannel 850. In the HBFET structure described herein, the current levelis dominated by the hetero-barrier energy barrier height (labeled H)between the source 825 and the energy barrier region 830. This barrierheight can be modulated by the gate voltage through the sidewall spacer.

According to one or more embodiments of the present invention, the HBFET1800 is a Si—SiGe structure with, the source 825, drain 827, and channel850 are composed of a strained silicon germanium (SiGe) or germanium(Ge). Further, the energy barrier 830 is composed of Si. The HBFET 1800further includes the gate stack 840 with side walls composed of spacermaterial such as Si3N4. In one or more examples, the regions are dopedto form a NPN HBFET such that—the source 825 and drain 827 are doped N+,and the energy barrier 830 and the channel 850 are doped P−. It shouldbe noted that in other examples the doping can be different to form aPNP HBFET.

FIG. 20 depicts an effect of the energy barrier in the SiGe—Si HBFETstructure 1800 described herein on the current level according to one ormore embodiments of the present invention. Plot 2010 depicts an ON stateof the HBFET and plot 2020 depicts an OFF state of the HBFET. In bothplots, a valence band 2035 and a conduction band 2045 are shown.Typically, in a diffusion FET, the “ON” state current is dominated bythe diffusion current from the source 825 to the drain 827, via thechannel 850. In the HBFET structure described herein, the current levelis dominated by the hetero-barrier energy barrier height (labeled H)between the source 825 and the energy barrier region 830. This barrierheight can be modulated by the gate voltage.

Further, in order to store the weight in the HBFET 1800, the gatepotential of the HBFET device 1800 is kept at a certain value. This canbe realized through different structures.

FIG. 21 depicts an embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention. The HBFET1800 is connected with a capacitor 1510. The charge is stored at theplate to provide the gate voltage, the charge stored beingrepresentative of the weight stored at the crosspoint in the RPU array600. It should be noted that only some of the parts of the HBFET device1800 are shown in FIG. 21 for simplicity of illustration.

FIG. 22 depicts an embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention. A chargestorage layer 1610, such as a floating gate is added to the gate stack840. The charge can be stored in the charge storing layer 1610 toprovide the gate voltage. The charge storing layer 1610 is composed ofpolysilicon. In one or more examples, another the gate dielectric layer841 is added after the charge storing layer 1610, followed by thefurther layers in the gate stack 840, such as the conductive materiallayer 842 for the electrode.

FIG. 23 depicts another embodiment to store the weight in the HBFET 1800according to one or more embodiments of the present invention. Here, thegate stack includes the gate dielectric layer 841 followed by a firstconductive material layer 842. A ferroelelectric material layer 1710 isadded subsequently, such as composed of hafnium dioxide (HfO2). Thepolarization of the ferroelectric layer 1710 induces electrical field inthe sidewall spacer to modulate the energy barrier height of layer 830.Further, the gate stack 840 includes a second conductive material layer842 to form the control gate electrode. The first conductive materiallayer 842 addresses a technical challenge of depolarization of theferroelelectric material layer 1710.

Further, in one or more examples, the energy barrier 830 between thesource 825 and the channel 850 is modulated in an indirect way, throughthe side wall 845 dielectrics. For example, the side walls 845 can becomposed of hafnium dioxide (HfO2) and titanium nitride (TiN)depositions are used to form a high-k dielectric layer. Theferroelectric layer 1710 and the side walls 845 thus form a metal highdielectric constant (MHK) gate stack.

Thus, the one or more planar HBFET semiconductor devices describedherein provide technical solutions to the technical challenges ofproviding controllable resistance, particularly above 10 MΩ. Such planarHBFETs can be used in crosspoint devices that are part of an RPU array600 that performs matrix multiplications, such as for implementing ANNs.

Further, according to one or more embodiments of the present invention,the semiconductor HBFET can be a vertical HBFET. FIG. 24 depicts anexample RPU array 600 using vertical semiconductor structure for theHBFET according to one or more embodiments of the present invention. TheRPU array 600 includes the vertical HBFET 2400 at each crosspoint alongwith additional circuitry at each cross-point (e.g. capacitor, weightupdate FETs, etc.). A cross-section view of the vertical HBFET 2400 isshown along an axis A-A′. The vertical HBFET 2400 can include the energybarrier 830 according to the one or more embodiments described herein(III-V, or SiGe—Si, or any other).

Herein, 802, 804, 806 are the top metal wires (row-wires) that contactthe top device terminals (drain 827 in this case). The bottom contact(source 825) is formed by the semiconductor layers grown on thesubstrate creating the active semiconductor regions 808, 810(column-wise). Furthermore, the vertical HBFET 2400 retains the varioussemiconductor layer stack as shown by the process steps in FIGS. 25-36.On the other hand, remaining region of 808, 810 outside of the HBFET2400 is etched down to p+ SiGe layer 2530 thus forming the common bottomconductor (column-wise) to HBFETs in regions 808, 810 (not shown).

The fabrication of the vertical HBFET 2400 in the RPU array 600 isdescribed further. The various illustrations used for the description ofthe fabrication method further uses cross-sectional views for each stepalong the A-A′ axis. The fabrication process is described for theSi—SiGe based structure, however a person skilled in the art can use thedescription for fabricating other types of the vertical HBFET asdescribed herein.

FIG. 25 depicts a substrate preparation of the HBFET 2400 area accordingto one or more embodiments of the present invention (in particular, withregard to FIG. 20). Initially, an HBFET region (for example, openingdevice region in STI) is defined on the substrate 2510. The substrate2510 can be any suitable substrate material, such as, for example, SiC,or semiconductor-on-insulator (SOI), or the like. In some embodiments,the substrate 2510 includes a buried oxide layer (not depicted). Thesemiconductor active region can be electrically isolated from otherregions of the substrate 2510 by a shallow trench isolation (STI) 2512.The STI 2512 can be of any suitable dielectric material, such as, forexample, a silicon oxide. Any known manner of forming the device todevice isolation 2512 can be utilized. In some embodiments, the STI 2512is formed by first depositing the dielectric material (2512) over theentire substrate and then opening the active semiconductor area 808, 810using an etch process which is then followed by the growth of additionalsemiconductor layers 2520, 2530, 2540, 2550, 2560 within theaforementioned opening. In some embodiments, the STI 2512 is formed byfirst growing the different semiconductor layers 2520, 2530, 2540, 2550,2560 over the entire substrate 2510 and then etching down to thesubstrate 2510 to form a trench, filling the trench with the STI 2512material, and planarizing to a surface of the semiconductor layer 2560using, for example, a CMP process.

Accordingly, a strain-relaxed-buffer (SRB) region 2520 is grown on thesubstrate 2510. Subsequently, a P+ SiGe (bottom source 825) 2530 isgrown on the SRB region 2520. A growth of the n− Si (hetero-barrier 830)layer 2540 is further performed. Subsequently, an N− SiGe (channel 850)layer 2550 is grown. Further, a P+ SiGe (top drain 827) layer 2560 isgrown. It should be noted that although the layers are depicted assource and drain, in other embodiments, the drain and source layers canbe interchanged.

For example, the heavily doped region 2530 of the substrate can be asource or drain region formed in the substrate 2510 by a variety ofmethods, such as, for example, in-situ doped epitaxy, doped followingthe epitaxy, or by implantation and plasma doping. The heavily dopedregion 2530 can be formed by any suitable process, including but notlimited to, ultrahigh vacuum chemical vapor deposition (UHVCVD), rapidthermal chemical vapor deposition (RTCVD), metalorganic chemical vapordeposition (MOCVD), low-pressure chemical vapor deposition (LPCVD),limited reaction processing CVD (LRPCVD), and MBE. In some embodiments,the heavily doped region 2530 includes epitaxial semiconductor materialsgrown from gaseous or liquid precursors. In some embodiments, epitaxialregions are epitaxially grown over the substrate 2510. Epitaxialsemiconductor materials can be grown using vapor-phase epitaxy (VPE),MBE, liquid-phase epitaxy (LPE), or other suitable processes. Epitaxialsilicon, SiGe, and/or carbon doped silicon (Si:C) can be doped duringdeposition (in-situ doped) by adding dopants, n-type dopants (e.g.,phosphorus or arsenic) or p-type dopants (e.g., Ga, B, BF₂, or Al). Thedopant concentration in the doped regions can range from 1×10¹⁹ cm⁻³ to2×10²¹ cm⁻³, or between 1×10²⁰ cm⁻³ and 1×10²¹ cm⁻³.

In some embodiments, the gas source for the deposition of epitaxialsemiconductor material includes a silicon containing gas source, agermanium containing gas source, or a combination thereof. For example,an epitaxial Si layer can be deposited from a silicon gas source that isselected from the group consisting of silane, disilane, trisilane,tetrasilane, hexachlorodisilane, tetrachlorosilane, dichlorosilane,trichlorosilane, methylsilane, dimethylsilane, ethylsilane,methyldisilane, dimethyldisilane, hexamethyldisilane and combinationsthereof. An epitaxial germanium layer can be deposited from a germaniumgas source that is selected from the group consisting of germane,digermane, halogermane, dichlorogermane, trichlorogermane,tetrachlorogermane and combinations thereof. An epitaxial silicongermanium alloy layer can be formed utilizing a combination of such gassources. Carrier gases like hydrogen, nitrogen, helium and argon can beused. In some embodiments, the doped regions include silicon. In someembodiments, the doped regions include carbon doped silicon (Si:C). ThisSi:C layer can be grown in the same chamber used for other epitaxy stepsor in a dedicated Si:C epitaxy chamber. The Si:C can include carbon inthe range of about 0.2 percent to about 3.0 percent.

FIG. 26 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention. In this step, using lithography techniques, avertical etch is performed to etch SiGe layers 2550 and 2560 until thefirst Si layer 2540. A mask using a predetermined dimensions is used forperforming the vertical etching to leave a drain and channel ofpredetermined dimensions.

For example, a hard mask is formed on a surface of each of thesemiconductor fins. The hard mask can include an oxide, nitride,oxynitride or any combination thereof, including multilayers. In someembodiments, the hard mask can include silicon oxide or silicon nitride.The hard mask can be formed utilizing a deposition process such as, forexample, chemical vapor deposition (CVD), plasma enhanced chemical vapordeposition (PECVD), chemical solution deposition, evaporation. In someembodiments, the hard mask can be formed by a thermal process such as,for example, oxidation or nitridation of the top semiconductor layer.Any combination of the above mentioned processes can also be used informing the hard mask. The hard mask can have a thickness from 20 nm to80 nm, for example, from 30 nm to 60 nm.

In some embodiments, the hard mask is formed prior to the semiconductorfins. The hard mask is then patterned and the pattern is transferred tothe substrate 2510 to form the semiconductor fins using knownlithographic processes. The lithographic step can include applying aphotoresist layer (not depicted) atop the hard mask, exposing thephotoresist layer to a desired pattern of radiation, and developing theexposed photoresist layer utilizing a resist developer. The etchingprocess can include dry etching and/or wet chemical etching. Examples ofdry etching processes that can be used include reactive ion etching(RIE), ion beam etching, plasma etching or laser ablation. The etchingprocess can transfer the pattern from the patterned photoresist layer tothe hard mask and to the substrate 2510. In some embodiments, a buriedinsulator layer (not depicted) serves as an etch stop. After forming thesemiconductor fins, the patterned photoresist layer can be removedutilizing a resist stripping process such as, for example, ashing. Insome embodiments, the semiconductor fins are formed utilizing a sidewallimage transfer (SIT) process (not depicted). In an SIT process, spacerscan be formed on a dummy mandrel. The dummy mandrel can be removed andthe remaining spacers can be used as a hard mask to etch the topsemiconductor layer. The spacers can then be removed after thesemiconductor fins have been formed.

FIG. 27 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention. In this step, using lithography techniques, avertical etch is performed to etch Si layer 2540 down to SiGe layer2530. Then a timed etching is performed on the SiGe layer 2530 of thesource 825. The etching is performed for a predetermined duration oftime, or to etch a predetermined depth S of the SiGe layer 2530. Theetching is performed as described herein.

FIG. 28 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention. In this step, material used to compose the sidewallspacers 845 of the gate stack 840 is deposited to form layer 2570. Thelayer 2570 is deposited in the vertically etched trenches on layer 2530that forms the source 825 as well as on the layer 2560 that forms thedrain 827. In one or more examples, an anisotropic etching is performedto have the spacer layer 2570 of a predetermined height above the layer2530.

The first bottom spacer 2570 can include a dielectric material, such assilicon oxide, silicon nitride, silicon oxynitride, or a combinationthereof, and can be formed using known deposition processes. In someembodiments, the first bottom spacer 2570 is formed by performing adirectional deposition process such as, for example, a Gas Cluster IonBeam (GCIB) process. The GCIB process is a deposition process that canbe highly directional in nature. For example, the directional depositionprocess can result in the deposition of dielectric material on thehorizontally oriented surfaces of the device, such as the upper surfaceof the hard mask and the substrate 2510, while avoiding deposition ofany substantial amount of dielectric material on the vertically-orientedsurfaces of the device, such as sidewalls of the semiconductor fins.

FIG. 29 depicts a subsequent intermediate structure of the HBFET 2400during the fabrication according to one or more embodiments of thepresent invention. In this step, a dielectric fill is performed todeposit an interlayer dielectric (ILD) material 2580 on exposed surfacesof the HBFET structure, for example, to fill regions between thesemiconductor fins. The ILD 2580 can be any suitable dielectricmaterial, such as, for example, a silicon oxide.

The ILD 2580 can be polished using, for example, CMP selective to thetop spacer (for example, stop on nitride). The CMP process can beutilized to remove excess portions of ILD 2580 such that the uppersurface of ILD 2580 is coplanar with the upper surface of the top spacer2570. In some embodiments, the material of ILD 2580 is chosen such thatportion of the top spacer 2570 and the hard mask can be removedselective to the ILD 2580 during a subsequent etching (as depicted inFIG. 30).

FIG. 30 depicts a cross-sectional view of a VFET structure after ILDopening during an intermediate operation of the exemplary method offabricating a semiconductor device according to one or more embodimentsof the invention. In some embodiments, a portion of the ILD 2580 isremoved to expose portions of the semiconductor fins. In anotherembodiment, as depicted in FIG. 30, ILD 2580 is removed down to thespacer material 2540 to expose portions of the semiconductor fins.

FIG. 31 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention. A high-k material layer 3110 is deposited on thebottom spacer 845 layer 2570, side wall of dielectric 2580 and the sidewall of semiconductor fin. The high-k material can be a dielectride suchas an HfO₂, or any suitable gate material to form the gate stack 840.The high dielectric gate oxide can be formed by, for example,deposition, over channel regions (i.e., sidewalls) of the semiconductorfins and the bottom spacer 845.

The high-k dielectric layer 3110 can be made of any suitable gatematerial, such as, for example, a high dielectric constant materialhaving a dielectric constant greater than silicon dioxide. Exemplaryhigh dielectric constant material include, for example, HfO2, ZrO2,La2O3, Al2O3, TiO2, SrTiO3, LaAlO3, Y2O3, HfOxNy, ZrOxNy, La2OxNy,Al2OxNy, TiOxNy, SrTiOxNy, LaAlOxNy, Y2OxNy, SiON, SiNx, a silicatethereof, and an alloy thereof, where each value of x is independentlyfrom 0.5 to 3 and each value of y is independently from 0 to 2.

Further, in one or more examples, a thin layer of metal, 3120, withspecific work function (WF-metal) can be deposited, followed by aconductive material layer 3130 (gate-fill metal). The thin metal layer3120 works to adjust the threshold voltage of the FET.

The gate conductor layer 3130 can be composed of metal and/orpolysilicon or any other material(s) that serves as the gate electrodefor the semiconductor device 2400. The conductive contact can be made ofany suitable conducting material, such as, for example, metal (e.g.,tungsten, titanium, tantalum, ruthenium, zirconium, cobalt, copper,aluminum, lead, platinum, tin, silver, gold), conducting metalliccompound material (e.g., tantalum nitride, titanium nitride, tantalumcarbide, titanium carbide, titanium aluminum carbide, tungsten silicide,tungsten nitride, ruthenium oxide, cobalt silicide, nickel silicide),carbon nanotube, conductive carbon, graphene, or any suitablecombination of these materials. The conductive material can furtherinclude dopants that are incorporated during or after deposition. Insome embodiments, the conductive contact 3130 can be copper and caninclude a barrier metal liner (not depicted). The barrier metal linerprevents the copper from diffusing into, or doping, the surroundingmaterials, which can degrade their properties. Silicon, for example,forms deep-level traps when doped with copper. An ideal barrier metalliner must limit copper diffusivity sufficiently to chemically isolatethe copper conductor from the surrounding materials and should have ahigh electrical conductivity, for example, tantalum nitride and tantalum(TaN/Ta), titanium, titanium nitride, cobalt, ruthenium, and manganese.

In one or more examples, the depositions can be performed by filling thetrench with the above layers and planarizing to a surface of the nitridelayer 2570 using, for example, a CMP process.

FIG. 32 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention. Following the deposition of the gate stack layers asdescribed earlier, an anisotropic etch of the gate-stack (high-k,WF-metal, gate-fill metal) is performed. The removal is performed usingany lithographic or etching methodology, such as, for example, a RIEselective to the lithographic hard-mask material being used.

FIG. 33 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention. The HBFET structure is filled with a top spacermaterial layer 3310. The top spacer material can be of the same materialthat was used in the layer 2570, and can include a dielectric material,such as silicon oxide, silicon nitride, silicon oxynitride, or acombination thereof, and can be formed using known deposition processes.In some embodiments, the spacer 3310 is deposited using a directionaldeposition process such as, for example, the GCIB process. Thedeposition is followed by a CMP process.

FIG. 34 depicts a cross-sectional view of a vertical HBFET structureduring the fabrication according to one or more embodiments of thepresent invention. Here, a middle of line processing is used to connectthe HBFET structure 2400 with the row-wires of the RPU array 600 (804 isshown). The middle of line (MOL) processing includes etching a contactthrough a liner which is the silicon nitride used in the spacer layerssuch as 2570 and 3310. The contact etch passes through the silicon oxidelayer and the silicon nitride layer to make contact with thesemiconductor region, and more particularly, the active crystallinesemiconductor region 2560 forming the drain 827. In regions wherecontacts to the bottom conducting layer 2530 are made (that form thecolumn-wise conductors 808, 810), the contact etch passes through thesilicon oxide layer and the silicon nitride layer to make contact withthe semiconductor layer 2530 (not shown).

In one or more examples, the MOL liner is deposited using plasmaenhanced chemical vapor deposition (PECVD) overlying the semiconductorstructure. By using a plasma enhanced chemical vapor deposition, theamount of MOL liner deposited in the core region and the peripheryregion can be controlled depending on the distances between transistorsin the core region and periphery region.

Further, in one or more examples, upon depositing the MOL liner, aninsulative layer (not shown) is deposited in-between the HBVFET and therow wire 802. For example, the insulative layer includes an insulativematerial, such as silicon nitride, silicon oxide, silicon oxynitride, orborophosphosilicate glass (BPSG). The insulative layer can be composedof more than one layer of insulative material.

Upon depositing the insulative layer, a contact etch is performedthrough the MOL liner. A contact etch 3410 is performed through thenitride layers 2570 and 3310. The contact etch 3410 allows an activecontact (CA), which overlies the surface of the semiconductor structure,to be electrically connected with the drain of the HBFET. Further, avertical interconnect layer (V0) 3420 is formed and deposited to connectthe contact 3410 with the row wire 804.

FIG. 35 depicts connections between the HBFET 2400 and the RPU array 600according to one or more embodiments of the present invention. FIG. 36depicts a cross-sectional view of a vertical HBFET structure during thefabrication according to one or more embodiments of the presentinvention to connect the HBFET 2400 to the RPU array 600. As describedearlier an active contact (CA) is created between the row wire 804 andthe terminal of the HBFET 2400 (FIG. 34). Further, by patterning theconducting material and using the MOL processing, a contact to the gate(CB) 3510 is created to connect the HBFET to the other circuitry 2410 atthe crosspoint of the RPU array 600, such as the capacitor 1510 etc. Thecapacitor 1510 can be the weight storage capacitor.

The VFET structure can be patterned using, for example, RIE. In someembodiments, the RIE is selective to the substrate 2510. The resultingstructure includes an energy barrier 830 as described herein.

The FET structures discussed so far include a gate structure, composedof polysilicon and/or a metal, formed on and contacting an insulatorplaced on top of the semiconductor layer positioned between the sourceand the drain. The semiconductor layer can include various dopantstherein, with one type of doping in the source and drain, and anothertype of doping in the channel and the energy barrier layer. By applyinga voltage to the gate structure, an electrically conductive channel canbe created within the semiconductor layer between the source and drainterminals. The energy barrier region 830 was fabricated in thesestructures to create a controllable high resistance.

In additional embodiments of the present invention, the FET structurecan use an alternative FET structure, known as a tunnel FET, whichincludes a gate contact separated from semiconductor layer by an oxidelayer. The semiconductor layer can include multiple types ofsemiconducting materials and dopants, such that controlling a voltage ofthe gate influences current flow between a source contact and a draincontact at two ends of the semiconductor layer. In such tunnel FETembodiments, compared to the diffusion FET and HBFET structures, wherethe source and drain are doped same type, the doping of the source anddrain of a tunneling FET are different types.

FIG. 37 depicts an embodiment of a tunnel FET 3700 according to one ormore embodiments of the present invention. The tunnel FET 3700, comparedto the diffusion FET described earlier (see FIG. 14, for example) doesnot include an energy barrier region 830. Instead, in the tunnel FET3700, the entire source terminal 825 is doped P+, different from thedrain terminal 827, which is doped N+ in the illustrated example. Itshould be noted that in other examples, the source terminal 825 can bedoped N+ and the drain terminal 827 is doped P+. Further, the channel850 is doped using the same dopant as the drain terminal, but with alighter concentration in comparison to the drain 827.

In one or more examples, the doping can be performed using ionimplantation, using patterned masks to cover one region while the otherregion is being doped. For example, the source terminal 825 can becovered while the drain terminal 827 is doped N+, and subsequently, thedrain terminal 827 is covered while the source terminal 825 is doped P+.

FIG. 38 depicts an effect of the tunnel FET structure described hereinon the current level according to one or more embodiments of the presentinvention. Plot 3810 depicts an ON state of a diffusion FET and plot3820 depicts an OFF state. In both plots, a valence band 3835 and aconduction band 3845 are shown. Typically, in a tunneling FET, the “ON”state current is dominated by the band to band tunneling of chargecarriers. The current level is determined by the shape of the barrierbetween source 825 and channel 850. The resistance of such FET can bemodulated by the doping of source 825 and channel 850 and is a functionof gate and drain bias.

FIG. 39 depicts an effect of the tunnel FET structure described hereinon the current level according to one or more embodiments of the presentinvention. The illustrated plot shows a comparison of a first transfercharacteristic 3910 of a typical FET, and a second transfercharacteristic 3920 of the tunnel FET 3700 with the source dopingdifferent than the drain and channel doping. As can be seen, the tunnelFET 3700 has a lower current. It should be noted that the plots in FIG.39 illustrate result values from one example scenario, and that in otherexamples, the plots can be different from those illustrated.

FIG. 40 depicts an effect of the energy barrier in the tunnel FETstructure described herein on the current level according to one or moreembodiments of the present invention. The illustrated plot showsresistance of the tunnel FET as a function of gate voltage withdifferent concentrations of doping at the source terminal 825. Forexample, the plot depicts the doping concentration at 4×10²⁰ cm⁻³(4010), 6×10²⁰ cm⁻³ (4020), 8×10²⁰ cm⁻³ (4030), and 1×10²¹ cm⁻³ (4040),respectively. It should be noted that the value the concentration can bedifferent from the above exemplary values, causing the FET resistance tochange in a different manner than what is shown in FIG. 40.

Referring back to FIG. 37, the tunnel FET structure further includes agate stack 840 (e.g., a gate dielectric layer 841, a gate conductorlayer 842 on the gate dielectric layer 841 and a cap layer 843, such asa nitride cap layer, on the gate conductor layer 842) over thedesignated channel region 850 within the device region. Further, gatesidewall spacers 845 are formed on opposing sides of the gate stack 840.

Further, in order to store the weight in the tunnel FET 3700, the gatepotential of the FET device 3700 is kept at a certain value. This can berealized through different structures.

FIG. 41 depicts an embodiment to store the weight in the tunnel FET 3700according to one or more embodiments of the present invention. Thetunnel FET 3700 is connected with a capacitor 1510, for example from theother circuitry 2410 at each of the crosspoints in RPU array 600. Thecharge is stored at the plate to provide the gate voltage, the chargestored being representative of the weight stored at the crosspoint inthe RPU array 600. It should be noted that only some of the parts of theFET device 3700 are shown in FIG. 41 for simplicity of illustration.

FIG. 42 depicts an embodiment to store the weight in the tunnel FET 3700according to one or more embodiments of the present invention. A chargestorage layer 1610, such as a floating gate is added to the gate stack840. The charge can be stored in the charge storing layer 1610 toprovide the gate voltage. The charge storing layer 1610 is composed ofpolysilicon. In one or more examples, another the gate dielectric layer841 is added after the charge storing layer 1610, followed by thefurther layers in the gate stack 840, such as the conductive materiallayer 842 for the electrode.

FIG. 43 depicts another embodiment to store the weight in the tunnel FET3700 according to one or more embodiments of the present invention.Here, the gate stack includes the gate dielectric layer 841 followed bya first conductive material layer 842. A ferroelelectric material layer1710 is added subsequently, such as composed of hafnium dioxide (HfO2).The polarization of the ferroelectric layer 1710 provides the gatevoltage. Further, the gate stack 840 includes a second conductivematerial layer 842 to form the control gate electrode. The firstconductive material layer 842 addresses a technical challenge ofdepolarization of the ferroelelectric material layer 1710.

The FET structures described herein provide an asymmetric structure, forexample because of the energy barrier 830, or the different doping ofthe source and drain/channel. Because of the asymmetric structure of thedevice, readout during forward and backward are applied in differentways.

FIG. 44 depicts a forward pass using the RPU array with the asymmetricFET structures described herein according to one or more embodiments ofthe present invention. As depicted, the RPU array 600 includes anasymmetric FET 4400 (diffusion FET 800, HBFET 1400, or tunnel FET 3700)at each crosspoint. During the forward pass voltage pulses 4420 areapplied at each row of the RPU array 600, and the resulting currents inthe columns are summed using current integrators 4410. In the forwardpath, the source terminal 825 of the FET 4400 is connected to thecurrent integrator 4410 of the corresponding column, and a positivepulse is applied to the drain terminal 827 of the FET 4400. Accordingly,the current via the FET 4400 is affected by the controllable resistanceof the FET 4400 during the forward pass.

FIG. 45 depicts a backward pass using the RPU array with the asymmetricFET structures described herein according to one or more embodiments ofthe present invention. As depicted, the RPU array 600 includes anasymmetric FET 4400 (diffusion FET 800, HBFET 1400, or tunnel FET 3700)at each crosspoint. During the backward pass voltage pulses 4420 areapplied at each column of the RPU array 600, and the resulting currentsin the rows are summed using current integrators 4410. During backwardpass, the base voltage at source 825 and drain 827 is shifted to apositive value +V. The drain terminal 827 of the FET 4400 is connectedto the current integrator 4410 of the corresponding row, and a negativepulse is applied to the source terminal 825 of the FET 4400.Accordingly, the current via the FET 4400 is affected by thecontrollable resistance of the FET 4400 during the backward pass.

Further, according to one or more embodiments of the present invention,the RPU array 600 can be implemented using symmetric FET structures. Thediffusion based FET 800 and the HBFET 1800, that include an energybarrier 830 can be fabricated with a substantially same energy barrier830′ on the drain side to make the FET device structure symmetric.

FIG. 46 depicts an example symmetric semiconductor structure for thediffusion FET according to one or more embodiments of the presentinvention. In this embodiment, the diffusion FET includes a pair ofenergy barriers, a first energy barrier 830 between the source 825 andthe channel 850, and a second energy barrier 830′ between the channel850 and the drain 827. The energy barrier regions 830 and 830′ arecomposed of the same material that is doped with heavier (higher)concentration than the channel 850.

FIG. 47 depicts an example symmetric semiconductor structure for theHBFET according to one or more embodiments of the present invention. Inthis embodiment, the HBFET includes a pair of energy barriers, a firstenergy barrier 830 between the source 825 and the channel 850, and asecond energy barrier 830′ between the channel 850 and the drain 827.The energy barrier regions 830 and 830′ are composed of the samematerial to form a hetero-barrier, such as indium phosphide (InP), orSi, depending on whether a III-V structure or a Si—SiGe structure isused.

Various embodiments of the present invention are described herein withreference to the related drawings. Alternative embodiments can bedevised without departing from the scope of this invention. Althoughvarious connections and positional relationships (e.g., over, below,adjacent, etc.) are set forth between elements in the followingdescription and in the drawings, persons skilled in the art willrecognize that many of the positional relationships described herein areorientation-independent when the described functionality is maintainedeven though the orientation is changed. These connections and/orpositional relationships, unless specified otherwise, can be direct orindirect, and the present invention is not intended to be limiting inthis respect. Similarly, the term “coupled” and variations thereofdescribes having a communications path between two elements and does notimply a direct connection between the elements with no interveningelements/connections between them. All of these variations areconsidered a part of the specification. Accordingly, a coupling ofentities can refer to either a direct or an indirect coupling, and apositional relationship between entities can be a direct or indirectpositional relationship. As an example of an indirect positionalrelationship, references in the present description to forming layer “A”over layer “B” include situations in which one or more intermediatelayers (e.g., layer “C”) is between layer “A” and layer “B” as long asthe relevant characteristics and functionalities of layer “A” and layer“B” are not substantially changed by the intermediate layer(s).

The following definitions and abbreviations are to be used for theinterpretation of the claims and the specification. As used herein, theterms “comprises,” “comprising,” “includes,” “including,” “has,”“having,” “contains” or “containing,” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, acomposition, a mixture, process, method, article, or apparatus thatcomprises a list of elements is not necessarily limited to only thoseelements but can include other elements not expressly listed or inherentto such composition, mixture, process, method, article, or apparatus.

Additionally, the term “exemplary” is used herein to mean “serving as anexample, instance or illustration.” Any embodiment or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments or designs. The terms “at least one”and “one or more” are understood to include any integer number greaterthan or equal to one, i.e. one, two, three, four, etc. The terms “aplurality” are understood to include any integer number greater than orequal to two, i.e. two, three, four, five, etc. The term “connection”can include an indirect “connection” and a direct “connection.”

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etc., indicate that the embodiment describedcan include a particular feature, structure, or characteristic, butevery embodiment may or may not include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to affect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

For purposes of the description hereinafter, the terms “upper,” “lower,”“right,” “left,” “vertical,” “horizontal,” “top,” “bottom,” andderivatives thereof shall relate to the described structures andmethods, as oriented in the drawing figures. The terms “overlying,”“atop,” “on top,” “positioned on” or “positioned atop” mean that a firstelement, such as a first structure, is present on a second element, suchas a second structure, wherein intervening elements such as an interfacestructure can be present between the first element and the secondelement. The term “direct contact” means that a first element, such as afirst structure, and a second element, such as a second structure, areconnected without any intermediary conducting, insulating orsemiconductor layers at the interface of the two elements.

The terms “about,” “substantially,” “approximately,” and variationsthereof, are intended to include the degree of error associated withmeasurement of the particular quantity based upon the equipmentavailable at the time of filing the application. For example, “about”can include a range of ±8% or 5%, or 2% of a given value.

The phrase “selective to,” such as, for example, “a first elementselective to a second element,” means that the first element can beetched and the second element can act as an etch stop.

The term “conformal” (e.g., a conformal layer) means that the thicknessof the layer is substantially the same on all surfaces, or that thethickness variation is less than 15% of the nominal thickness of thelayer.

The terms “epitaxial growth and/or deposition” and “epitaxially formedand/or grown” mean the growth of a semiconductor material (crystallinematerial) on a deposition surface of another semiconductor material(crystalline material), in which the semiconductor material being grown(crystalline overlayer) has substantially the same crystallinecharacteristics as the semiconductor material of the deposition surface(seed material). In an epitaxial deposition process, the chemicalreactants provided by the source gases can be controlled and the systemparameters can be set so that the depositing atoms arrive at thedeposition surface of the semiconductor substrate with sufficient energyto move about on the surface such that the depositing atoms orientthemselves to the crystal arrangement of the atoms of the depositionsurface. An epitaxially grown semiconductor material can havesubstantially the same crystalline characteristics as the depositionsurface on which the epitaxially grown material is formed. For example,an epitaxially grown semiconductor material deposited on a {100}orientated crystalline surface can take on a {100} orientation. In someembodiments of the invention, epitaxial growth and/or depositionprocesses can be selective to forming on semiconductor surface, and mayor may not deposit material on exposed surfaces, such as silicon dioxideor silicon nitride surfaces.

As previously noted herein, for the sake of brevity, conventionaltechniques related to semiconductor device and integrated circuit (IC)fabrication may or may not be described in detail herein. By way ofbackground, however, a more general description of the semiconductordevice fabrication processes that can be utilized in implementing one ormore embodiments of the present invention will now be provided. Althoughspecific fabrication operations used in implementing one or moreembodiments of the present invention can be individually known, thedescribed combination of operations and/or resulting structures of thepresent invention are unique. Thus, the unique combination of theoperations described in connection with the fabrication of asemiconductor device according to the present invention utilize avariety of individually known physical and chemical processes performedon a semiconductor (e.g., silicon) substrate, some of which aredescribed in the immediately following paragraphs.

In general, the various processes used to form a micro-chip that will bepackaged into an IC fall into four general categories, namely, filmdeposition, removal/etching, semiconductor doping andpatterning/lithography. Deposition is any process that grows, coats, orotherwise transfers a material onto the wafer. Available technologiesinclude physical vapor deposition (PVD), chemical vapor deposition(CVD), electrochemical deposition (ECD), molecular beam epitaxy (MBE)and more recently, atomic layer deposition (ALD) among others.Removal/etching is any process that removes material from the wafer.Examples include etch processes (either wet or dry), chemical-mechanicalplanarization (CMP), and the like. Reactive ion etching (RIE), forexample, is a type of dry etching that uses chemically reactive plasmato remove a material, such as a masked pattern of semiconductormaterial, by exposing the material to a bombardment of ions thatdislodge portions of the material from the exposed surface. The plasmais typically generated under low pressure (vacuum) by an electromagneticfield. Semiconductor doping is the modification of electrical propertiesby doping, for example, transistor sources and drains, generally bydiffusion and/or by ion implantation. These doping processes arefollowed by furnace annealing or by rapid thermal annealing (RTA).Annealing serves to activate the implanted dopants. Films of bothconductors (e.g., poly-silicon, aluminum, copper, etc.) and insulators(e.g., various forms of silicon dioxide, silicon nitride, etc.) are usedto connect and isolate transistors and their components. Selectivedoping of various regions of the semiconductor substrate allows theconductivity of the substrate to be changed with the application ofvoltage. By creating structures of these various components, millions oftransistors can be built and wired together to form the complexcircuitry of a modern microelectronic device. Semiconductor lithographyis the formation of three-dimensional relief images or patterns on thesemiconductor substrate for subsequent transfer of the pattern to thesubstrate. In semiconductor lithography, the patterns are formed by alight sensitive polymer called a photo-resist. To build the complexstructures that make up a transistor and the many wires that connect themillions of transistors of a circuit, lithography and etch patterntransfer steps are repeated multiple times. Each pattern being printedon the wafer is aligned to the previously formed patterns and slowly theconductors, insulators and selectively doped regions are built up toform the final device.

The flowchart and block diagrams in the Figures illustrate possibleimplementations of fabrication and/or operation methods according tovarious embodiments of the present invention. Variousfunctions/operations of the method are represented in the flow diagramby blocks. In some alternative implementations, the functions noted inthe blocks can occur out of the order noted in the Figures. For example,two blocks shown in succession can, in fact, be executed substantiallyconcurrently, or the blocks can sometimes be executed in the reverseorder, depending upon the functionality involved.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments described. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdescribed herein.

What is claimed is:
 1. A method for forming a semiconductor device, themethod comprising: forming a source terminal of a semiconductor fin on asubstrate; forming an energy barrier on a surface of the sourceterminal; forming a channel on a surface of the energy barrier; forminga drain terminal on a surface of the channel; recessing the drainterminal and the channel on either sides of the channel; etching theenergy barrier in recesses formed by the recessing; recessing the sourceterminal using timed etching to remove a portion of the source terminalin recesses formed by etching the energy barrier; forming a first bottomspacer on a surface of the source terminal and a sidewall of thesemiconductor fin; and forming a gate stack on a surface of the firstbottom spacer.
 2. The method of claim 1 further comprising: etching thegate stack; forming a second bottom spacer on a surface of the gatestack; forming an active contact connecting the drain terminal with afirst line; and forming a gate contact connecting the gate stack with asecond line.
 3. The method of claim 1, wherein the first bottom spaceris composed of a silicon nitride, the drain terminal and the sourceterminal are composed of P+ doped SiGe, and the channel is composed ofN− doped SiGe, and the energy barrier is composed of Si.